In magnetic storage systems for computers, digital data serves to modulate the current in a read/write head coil so that a sequence of corresponding magnetic flux transitions are written onto a magnetic medium in concentric tracks at a predetermined baud rate. When reading this recorded data, the read/write head again passes over the magnetic medium and transduces the magnetic transitions into pulses in an analog signal that alternate in polarity. These pulses are then decoded by read channel circuitry to reproduce the digital data.
Decoding the pulses into a digital sequence can be performed by a simple peak detector in a conventional analog read channel or, as in more recent designs, by a discrete time sequence detector in a sampled amplitude read channel. Discrete time sequence detectors are preferred over simple analog pulse detectors because they compensate for intersymbol interference (ISI) and are less susceptible to noise. As a result, discrete time sequence detectors increase the capacity and reliability of the storage system.
There are several well known discrete time sequence detection methods including discrete time pulse detection (DPD), partial response (PR) with Viterbi detection, maximum likelihood sequence detection (MLSD), decision-feedback equalization (DFE), enhanced decision-feedback equalization (EDFE), and fixed-delay tree-search with decision-feedback (FDTS/DF).
In conventional peak detection schemes, analog circuitry, responsive to threshold crossing or derivative information, detects peaks in the continuous time analog signal generated by the read head. The analog read signal is "segmented" into bit cell periods and interpreted during these segments of time. The presence of a peak during the bit cell period is detected as a "1" bit, whereas the absence of a peak is detected as a "0" bit. The most common errors in detection occur when the bit cells are not correctly aligned with the analog pulse data. Timing recovery, then, adjusts the bit cell periods so that the peaks occur in the center of the bit cells on average in order to minimize detection errors. Since timing information is derived only when peaks are detected, the input data stream is normally run length limited (RLL) to limit the number of consecutive "0" bits.
As the pulses are packed closer together on the concentric data tracks in the effort to increase data density, detection errors can also occur due to intersymbol interference, a distortion in the read signal caused by closely spaced overlapping pulses. This interference can cause a peak to shift out of its bit cell, or its magnitude to decrease, resulting in a detection error. The ISI effect is reduced by decreasing the data density or by employing an encoding scheme to ensure that a minimum number of "0" bits occur between "1" bits. For example, a (d,k) run length limited (RLL) code constrains to d the minimum number of "0" bits between "1" bits, and to k the maximum number of consecutive "0" bits. A typical RLL (1,7) 2/3 rate code encodes 8 bit data words into 12 bit codewords to satisfy the (1,7) constraint.
Sampled amplitude detection, such as partial response (PR) with Viterbi detection, allows for increased data density by compensating for intersymbol interference and increasing channel noise immunity. Unlike conventional peak detection systems, sampled amplitude recording detects digital data by interpreting, at discrete time instances, the actual value of the pulse data. A sampling device samples the analog read signal at the baud rate (code bit rate) and an equalizing filter equalizes the sample values according to a desired partial response. A discrete time sequence detector, such as a Viterbi detector, interprets the equalized sample values in context to determine a most likely sequence for the data (i.e., maximum likelihood sequence detection MLSD). In this manner, the effect of ISI and channel noise can be taken into account during the detection process, thereby decreasing the probability of a detection error. This increases the effective signal to noise ratio and, for a given (d,k) constraint, allows for significantly higher data density as compared to conventional analog peak detection read channels.
The application of sampled amplitude techniques to digital communication channels is well documented. See Y. Kabal and S. Pasupathy, "Partial Response Signaling", IEEE Trans. Commun. Tech., Vol. COM-23, pp. 921-934, Sept. 1975; and Edward A. Lee and David G. Messerschmitt, "Digital Communication", Kluwer Academic Publishers, Boston, 1990; and G. D. Forney, Jr., "The Viterbi Algorithm", Proc. IEEE, Vol. 61, pp. 268-278, March 1973.
Applying sampled amplitude techniques to magnetic storage systems is also well documented. See Roy D. Cideciyan, Francois Dolivo, Walter Hirt, and Wolfgang Schott, "A PRML System for Digital Magnetic Recording", IEEE Journal on Selected Areas in Communications, Vol. 10 No. 1, January 1992, pp. 38-56; and Wood et al, "Viterbi Detection of Class IV Partial Response on a Magnetic Recording Channel", IEEE Trans. Commun., Vol. Com-34, No. 5, pp. 454-461, May 1986; and Coker Et al, "Implementation of PRML in a Rigid Disk Drive", IEEE Trans. on Magnetics, Vol. 27, No. 6, Nov. 1991; and Carley et al, "Adaptive Continous-Time Equalization Followed By FDTS/DF Sequence Detection", Digest of The Magnetic Recording Conference, Aug. 15-17, 1994, pp. C3; and Moon et al, "Constrained-Complexity Equalizer Design for Fixed Delay Tree Search with Decision Feedback", IEEE Trans. on Magnetics, Vol. 30, No. 5, Sept. 1994; and Abbott et al, "Timing Recovery For Adaptive Decision Feedback Equalization of The magnetic Storage Channel", Globecom'90 IEEE Global Telecommunications Conference 1990, San Diego, Calif., Nov. 1990, pp. 1794-1799; and Abbott et al, "Performance of Digital Magnetic Recording with actualization and Offtrack Interference", IEEE Transactions on Magnetics, Vol. 27, No. 1, Jan. 1991; and Cioffi et al, "Adaptive Equalization in Magnetic-Disk Storage Channels", IEEE Communication Magazine, Feb. 1990; and Roger Wood, "Enhanced Decision Feedback Equalization", Intermag'90.
Similar to conventional peak detection systems, sampled amplitude detection requires timing recovery in order to correctly extract the digital sequence. Rather than process the continuous signal to align peaks to the center of bit cell periods as in peak detection systems, sampled amplitude systems synchronize the pulse samples to the baud rate. In prior art sampled amplitude read channels, timing recovery synchronizes a sampling clock by minimizing an error between the signal sample values and estimated sample values. A pulse detector or slicer determines the estimated sample values from the read signal samples. Even in the presence of ISI the sample values can be estimated and, together with the signal sample values, used to synchronize the sampling of the analog pulses in a decision-directed feedback system.
A phase-locked-loop (PLL) normally implements the decision-directed feedback system to control timing recovery in sampled amplitude read channels. A phase detector generates a phase error based on the difference between the estimated samples and the read signal samples. A loop filter filters the phase error, and the filtered phase error operates to synchronize the channel samples to the baud rate.
In prior art timing recovery methods, the phase error adjusts the frequency of a sampling clock which is typically the output of a variable frequency oscillator (VFO) . The output of the VFO controls a sampling device, such as an analog-to-digital (A/D) converter, to synchronize the pulse samples to the baud rate.
Also in prior art timing recovery methods, it is helpful to first lock the PLL to a reference or nominal sampling frequency so that the desired sampling frequency, with respect to the analog pulses representing the digital data, can be acquired and tracked more efficiently. The nominal sampling frequency is the baud rate, the rate that data was written onto the medium. Therefore, one method to lock-to-reference is to generate a sinusoidal signal relative to the output of a write VFO (write clock) and inject this signal into the PLL. Once locked to the reference frequency, the PLL input switches from the write clock to the signal from the read head in order to synchronize the sampling of the waveform in response to a sinusoidal acquisition preamble recorded on the medium.
The acquisition and tracking modes for timing recovery are related to the data format of the magnetic disk. FIG. 2A shows a magnetic disk comprising a plurality of concentric data tracks 13 wherein each data track 13 is comprised of a plurality of sectors 15. Servo data in the form of wedges 17 are embedded into the sectors 15 and used to control and verify the track and sector position of the read/write head. FIG. 2B shows the format of a sector 15 comprising an acquisition preamble 68, a sync mark 70, and user data 72. The acquisition preamble is a predetermined sequence that allows timing recovery to acquire the desired sampling phase and frequency before reading the user data. After acquisition, the PLL switches to a tracking mode in order to track the desired sampling phase and frequency with respect to the analog pulses representing the user data. The sync mark signals the beginning of the user data. As illustrated in FIG. 2B, a short acquisition preamble is desirable to allow more storage area for user data.
Zoned recording is a technique known in the art for increasing the storage density by recording the user data at different rates in predefined zones between the inner diameter and outer diameter tracks. The data rate can be increased at the outer diameter tracks due to the increase in circumferential recording area and the decrease in intersymbol interference. This allows more data to be stored in the outer diameter tracks as is illustrated in FIG. 2A where the disk is partitioned into an outer zone 11 comprising fourteen data sectors per track, and an inner zone 27 comprising seven data sectors per track. In practice, the disk may actually be partitioned into several zones at varying data rates.
Prior techniques are known for acquiring and tracking the sampling frequency/phase based on the phase error computed from the actual signal samples and estimated signal samples obtained from symbol-by-symbol decisions. See "Timing Recovery in Digital Synchronous Receivers" by K. H. Mueller and M. Muller, IEEE Transactions on Communications, vol. Com-24 (1976), pp. 516-531. Co-pending United States patent application Ser. No. 08/313,491 entitled "Improved Timing Recovery for Synchronous Partial Response Recording" discloses an improvement to the Mueller and Muller stochastic gradient method. In this method of timing recovery a slicer, commonly employed in a d=0 PR4 partial response recording channel, estimates the sample values by comparing the signal sample values to predetermined thresholds. A stochastic gradient circuit, which minimizes the mean squared error between the signal sample values and the estimated sample values, generates the phase error to control the frequency of the sampling VFO.
U.S. Pat. No. 5,359,631 entitled "Timing Recovery Circuit for Synchronous Waveform Sampling" discloses yet another method for timing recovery in a sampled amplitude read channel. In this method a pulse detector, commonly employed in a d=1 EPR4 or EEPR4 partial response recording channel, operates to determine the estimated sample values. Again, a stochastic gradient circuit uses the estimated sample values, together with the signal sample values, to generate the phase error for adjusting the sampling clock in the decision-directed feedback system.
The timing recovery loop filter controls the dynamics of the decision-directed feedback system. Accordingly, the loop filter coefficients are adjusted to achieve a desired transient response and tracking quality. For good tracking quality, the loop bandwidth should be narrow so that phase noise and gain variance is attenuated. During acquisition, the loop bandwidth should be as wide as possible without being unstable to achieve a fast transient response. A fast transient response results in a shorter acquisition time which minimizes the necessary length of the acquisition preamble.
Several problems have been identified with timing recovery methods that synchronize sampling of the pulses using a variable frequency oscillator in a PLL. For instance, the slight difference in operating frequencies between the write VFO and the sampling VFO results in cross-talk that degrades the performance of timing recovery. Further, synchronous detection of embedded servo data requires an additional servo VFO to generate the center operating frequency of the sampling VFO when reading the servo data (see the above referenced U.S. patent entitled "Samples Amplitude Read Channel Employing a User Data Frequency Synthesizer and a Servo Data Frequency Synthesizer"). Yet another problem associated with conventional PLL timing recovery are the delays inherent in the sampling device and discrete time equalizing filter which cause the timing loop to be less stable. Thus, latency considerations can increase the cost and complexity of the sampling device and reduce the effectiveness of the equalizing filter. A more complex discrete time equalizing filter could equalize the samples before the timing loop, but this would require reconstruction at the filter's output from discrete-time back to continuous-time for processing by the sampling PLL.
There is, there-ore, a need for a new timing recovery technique for sampled amplitude recording that does not exhibit the cross talk phenomena associated with a write VFO frequency being very near a sampling VFO frequency. A further object is to avoid using a separate servo VFO for reading embedded servo data. Yet another object is to remove the sampling device and discrete time equalizing filter, and their associated latencies, from the timing recovery loop.